Currently known minimally invasive procedures for diagnosis and treatment of medical conditions use shapeable instruments, such as steerable devices, flexible catheters or more rigid arms or shafts, to approach and address various tissue structures within the body. For various reasons, it is highly valuable to be able to determine the 3-dimensional spatial position of portions of such shapeable instruments relative to other structures, such as the operating table, other instruments, or pertinent anatomical tissue structures. Such information can be used for a variety of reasons, including, but not limited to: improve device control; to improve mapping of the region; to adapt control system parameters (whether kinematic and/or solid mechanic parameters); to estimate, plan and/or control reaction forces of the device upon the anatomy; and/or to even monitor the system characteristics for determination of mechanical problems. Alternatively, or in combination, shape information can be useful to simply visualize the tool with respect to the anatomy or other regions, whether real or virtual.
In many conventional systems, the catheter (or other shapeable instrument) is controlled in an open-loop manner, as described in U.S. patent Ser. No. 12/822,876, the contents of which are incorporated by reference in its entirety. However, at times the assumed motion of the catheter does not match the actual motion of the catheter. One such reason for this issue is the presence of unanticipated or unmodeled constraints imposed by the patient's anatomy. Another reason for this may be that the parameters of the tool do not meet the ideal/anticipated parameters because of manufacturing tolerances or changes in the mechanical properties of the tool from the environment and aging.
Thus to perform certain desired applications, such as, for example, instinctive driving, shape feedback, and driving in a fluoroscopy view or a model, there exists a need for tool sensors to be properly registered to the patient in real time. Moreover, there remains a need to apply the information gained by spatial information or shape and applying this information to produce improved device control or improved modeling when directing a robotic or similar device. There also remains a need to apply such controls to medical procedures and equipment.
Localization sensors such as fiber optic shape sensors may include Incremental Measurement Sensors (IMSs). An IMS measures a shape or path of an elongate member by combining a sequence of serial orientation and distance measurements. For instance, FOSSL generates a shape by measuring types of strain at discrete points in the fiber; this strain is then translated to the incremental change in roll and bend, which is incremented along all steps to obtain the position and orientation at a given location. As a result, each position and orientation at a point is dependent on the position and orientation of all proceeding points. In contrast, an electromagnetic coil sensor measures position at points along the elongate member independent of any other measurements.
One drawback of IMSs is that a measurement noise (error) at any location along the path may propagate to all measurements distal to that measurement. While these errors are implicit in the nature of the sensor, orientation errors at a proximal portion of the IMS may result in a large position error at the distal end of the elongate member. In applications that include accurate distal position measurements, this can cause the measured tip position to vary greatly between successive measurements due to noise at a single point in the proximal portion. One way of thinking about the issue is to consider the IMS length as a lever arm—small rotations at one end cause large changes in the position at the other end. The longer the lever arm, the more pronounced the conversion from proximal orientation error to distal position error. It should be noted that an orientation error at the proximal end will not tend to cause a large orientation error at the distal end because orientation errors themselves accumulate (sum) over the length of the sensor.
Thus, for Incremental Measurement Sensors that build a shape using a sequence of small orientation measurements, a small error in orientation at the proximal end of the sensor will cause a large error in position at distal points on the fiber. Accordingly, there is a need for an improved method of using IMSs that reduces measurement errors.